Add task category, paper and code links (#1)

- Add task category, paper and code links (281dc556fed09a6f7abc8f1d89cfdba6172e32d5)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,3 +1,25 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- image-to-3d
+tags:
+- slam
+- 3d-reconstruction
+- monocular
+---
+
+This repository contains data for WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments.
+
+[Paper](https://huggingface.co/papers/2504.03886) | [Project Page](https://wildgs-slam.github.io/) | [Code](https://github.com/GradientSpaces/WildGS-SLAM)
+
+WildGS-SLAM accurately tracks the camera trajectory and reconstructs a 3D Gaussian map for static elements from a monocular video sequence, effectively removing dynamic components.
+
+
+### Datasets Used
+
+WildGS-SLAM uses data from the following datasets:
+
+* **Wild-SLAM Mocap Dataset:** ([Hugging Face](https://huggingface.co/datasets/gradient-spaces/Wild-SLAM/tree/main/Mocap))  Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).
+* **Wild-SLAM iPhone Dataset:** ([Hugging Face](https://huggingface.co/datasets/gradient-spaces/Wild-SLAM/tree/main/iPhone)) Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).
+* **Bonn Dynamic Dataset:** ([Website](https://www.ipb.uni-bonn.de/data/rgbd-dynamic-dataset/index.html)) Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).
+* **TUM RGB-D (dynamic) Dataset:** Download instructions are available in the [github repository](https://github.com/GradientSpaces/WildGS-SLAM).